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A Library which provides more information about suitable Machine learning algorithm for your dataset

Project description

Model Selection

Scope of This Project

  • As a beginner in Data science/Machine learning field, most of us having issue in Feature Selection, Feature Extraction and Model Selection. Algorithm-Finder can help you to solve this problem. using Algorithm-Finder you can achieve the below tasks and more.

    • Model Selection
    • Feature Selection
    • Feature Extraction
    • Optimized tuning parameters
  • This package mainly used scikit-learn for most of the estimators, by using Algorithm-Finder you can apply your dataset on below models

    • ALL --> ALL IN
    • MLR --> MultiLinearRegression
    • POLY --> PolynomialRegression
    • SVR --> SupportVectorRegression
    • DTREE --> DecisionTreeRegression & DecisionTreeClassification
    • RFR --> RandomForestRegression
    • SIGMOID --> LogisticRegression
    • KNN --> K-NearestNeighbours Classifier
    • SVM --> SupportVectorMachine Classifier
    • RFC --> RandomForestClassifier
    • BAYESIAN --> NaiveBayesClassifier

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